R Notebook for team selection

Team selection tool for Informationsvisualisering

###Install packages
install.packages("tidyverse")

WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/
Installing package into 㤼㸱C:/Users/c3i2/Documents/R/win-library/4.0㤼㸲
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library(tidyverse)

package 㤼㸱tidyverse㤼㸲 was built under R version 4.0.3-- Attaching packages --------------------------------------- tidyverse 1.3.0 --
v ggplot2 3.3.2     v purrr   0.3.4
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v tidyr   1.1.0     v stringr 1.4.0
v readr   1.3.1     v forcats 0.5.0
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install.packages("plotly")

WARNING: Rtools is required to build R packages but is not currently installed. Please download and install the appropriate version of Rtools before proceeding:

https://cran.rstudio.com/bin/windows/Rtools/
Installing package into 㤼㸱C:/Users/c3i2/Documents/R/win-library/4.0㤼㸲
(as 㤼㸱lib㤼㸲 is unspecified)
trying URL 'https://cran.rstudio.com/bin/windows/contrib/4.0/plotly_4.9.3.zip'
Content type 'application/zip' length 3118743 bytes (3.0 MB)
downloaded 3.0 MB

package ‘plotly’ successfully unpacked and MD5 sums checked

The downloaded binary packages are in
    C:\Users\c3i2\AppData\Local\Temp\RtmpgVh5xE\downloaded_packages

library(plotly)

package 㤼㸱plotly㤼㸲 was built under R version 4.0.3
Attaching package: 㤼㸱plotly㤼㸲

The following object is masked from 㤼㸱package:ggplot2㤼㸲:

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### load data
Project_2 <- read.csv("~/Project_2.csv", sep=";", comment.char="#")
head(Project_2)

Instructions

• Identify your own weaknesses
• Pick somebody that complements you - strong where you are weak on one of the graphs
• Iteratively keep selecting persons that are different then the current team from the three graphs

Plot1 <- ggplot(data = Project_2, aes(x=Statistical.skills, y=Programming.skills, group = 1, text = paste("Alias: ", Alias, "<br>Interests:", Interests )
)) + theme_bw()+
      geom_jitter(width = 0.2, height = 0.2, alpha = 0.5)+
### jitter added to avoid overplotting
ggtitle("Students in Information Visualization - Hard skills")+
  ylab("Programming skills")+
  xlab("Statistical skills")
  
ggplotly(Plot1)

### color (categorical) removed to simplify

Plot2 <- ggplot(data = Project_2, aes(x=Communication.skills, y=Collaboration.skills,  group = 1, text = paste("Alias: ", Alias, "<br>Interests:", Interests )
)) + theme_bw()+
  geom_jitter(width = 0.2, height = 0.2, alpha = 0.5)+
  ### jitter added to avoid overplotting
  ggtitle("Students in Information Visualization - Soft skills")+
  ylab("Collaboration skills")+
  xlab("Communication skills")
ggplotly(Plot2)

### color (categorical) removed to simplify

Plot3 <- ggplot(data = Project_2, aes(x=Graphics.programming.skills, y=User.experience.evaluation.skills,  group = 1, text = paste("Alias: ", Alias, "<br>Interests:", Interests )
)) + theme_bw()+
  geom_jitter(width = 0.2, height = 0.2, alpha = 0.5)+
### jitter added to avoid overplotting
  ggtitle("Students in Information Visualization - Unicorn skills")+
  ylab("Graphics programming skills")+
  xlab("UX evaluation skills")
ggplotly(Plot3)

### color (categorical) removed to simplify